• DocumentCode
    1847690
  • Title

    Particle swarm optimization (PSO) technique in economic power dispatch problems

  • Author

    Jaini, A. ; Musirin, I. ; Aminudin, N. ; Othman, M.M. ; Rahman, T.K.A.

  • Author_Institution
    Univ. Teknol. MARA, Shah Alam, Malaysia
  • fYear
    2010
  • fDate
    23-24 June 2010
  • Firstpage
    308
  • Lastpage
    312
  • Abstract
    Economic power dispatch problem plays an important role in the operation of the power systems. It is a method of determine the most efficient, low cost and reliable operation of a power system by dispatching the available electricity generation resources to supply the load on the system. The primary objective of economic dispatch is to minimize the total cost of generation while maintaining the operational constraints of the available generation resources. In this paper, a particle swarm optimization algorithms (PSO) with one of the accelerating coefficients being constant are proposed to solve the economic power dispatch problem. Particle swarm optimization (PSO) is algorithms modeled on swarm intelligence that finds a solution to an optimization problem in a search space, or model and predict social behavior in the presence of objectives. In this study, the proposed technique was tested using the standards IEEE 26-BUS RTS and the results revealed that the proposed technique has the merit in achieving optimal solution for addressing the problems.
  • Keywords
    particle swarm optimisation; power generation dispatch; power generation economics; economic power dispatch problem; electricity generation resources; particle swarm optimization; Cost function; Economics; Generators; Particle swarm optimization; Power engineering; Power systems; Economic dispatch; optimization; particle swarm optimization; power system;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Power Engineering and Optimization Conference (PEOCO), 2010 4th International
  • Conference_Location
    Shah Alam
  • Print_ISBN
    978-1-4244-7127-0
  • Type

    conf

  • DOI
    10.1109/PEOCO.2010.5559236
  • Filename
    5559236